Tree canopy
Population-based Scenario: AI: Increase by 10% in all zip codes
Targeted
Scenario AII1: Increase by 10% in zip codes in the lowest 1/5th of current TC cover (i.e. <=20th pctile)
Scenario AII2: Increase by 10% in zip codes in the highest 1/5th of the Social Vulnerability Index (i.e. >80th pctile)
Scenario AII3: Increase by 10% in zip codes in the highest 1/5th of hospitalization burden (i.e. >80th pctile)
Proportionate-universalism
Scenario AIII1: Increase by 10% for bottom 1/5th of current TC cover… down to 2% for top 1/5th
Scenario AIII2: Increase by 10% for top 1/5th of SVI … down to 2% for bottom 1/5th
Scenario AIII3: Increase by 10% for top 1/5th of hospitalization burden … down to 2% for bottom 1/5th
Impervious surface cover
Population-based: Scenario BI: Decrease by 10% in all zip codes
Targeted
Scenario BII1: Decrease by 10% in zip codes in the highest 1/5th of current imperv cover (i.e. >80th pctile)
Scenario BII2: Decrease by 10% in zip codes in the highest 1/5th of the Social Vulnerability Index (i.e. >80th pctile)
Scenario BII3: Decrease by 10% in zip codes in the highest 1/5th of hospitalization burden (i.e. >80th pctile)
Proportionate-universalism
Scenario BIII1: Decrease by 10% for top 1/5th of current imperv cover … down to 2% for bottom 1/5th
Scenario BIII2: Decrease by 10% for top 1/5th of SVI … down to 2% for bottom 1/5th
Scenario BIII3: Decrease by 10% for top 1/5th of hospitalization burden … down to 2% for bottom 1/5th
The following maps visualize, for each scenario, ratio-based and difference-based effect estimates on hospitalizations in California at the level of the zip-code tabulation area.
Ratio
Difference